Proactive prevention is a strengths-based approach, where services engage with at-risk patients when their acuity levels are low and there is more time to deal with social care challenges and build stronger engagement with providers across the board.

These stronger connections then stand in good stead when health crises arrive, allowing health services to then be more effective.

In collaboration with the Institute for Urban Indigenous Health (IUIH), the project team investigate the possible use of a machine learning tool to help identify patients at an Aboriginal and Torres Strait Islander primary care clinic who are at greatest need and could benefit from a proactive prevention programme to prevent exacerbation of health conditions.

The first part of this research was supported by the UQ Poche Centre for Indigenous Health through their Research Collaboration Seeding Grant. During the first phase of the project, preliminary models are developed.

With the support of UQ AI Collaboratory co-design meetings, case reviews are conducted and the current process, requirements for model refinement are identified. Once an acceptable model is built, the next step of this project is to working towards a deployable tool within the system used by clinicians.

Project members

Dr Gayani Tennakoon Mudiyanselage

Research Fellow in Data Scienc
Institute for Social Science Research

Professor Rhema Vaithianathan

Professor of Health Economics at AUT

Ms Laura Cleator

Institute for Urban Indigenous Health

Dr Lyle Turner

Institute for Urban Indigenous Health

Dr Saira Mathew

Institute for Urban Indigenous Health